MLOPS Engineer
Location: Concord, CA (100% Onsite )
Hire Type: Contract
Employment Eligibility: GC and USC
Role Summary
Seeking a Senior MLOps Engineer to build, deploy, and operate production-grade ML systems . This role focuses on automating the ML lifecycle , enabling scalable cloud deployments , and ensuring model reliability, monitoring, and governance in an enterprise environment.
Key Responsibilities
Build and maintain end-to-end ML pipelines using MLflow, Kubeflow, or Vertex AI
Automate model training, testing, deployment, monitoring, and retraining
Implement CI/CD workflows for model versioning and lifecycle management
Deploy ML workloads on Google Cloud Platform, AWS, or Azure using Docker and Kubernetes
Monitor model performance, drift, and compliance with model governance (MRM, explainability)
Support low-latency inference APIs for real-time and batch scoring
Leverage AutoML tools (Vertex AI AutoML, H2O Driverless AI) for rapid model delivery
Required Qualifications
10+ years in Software Engineering and 3+ years in MLOps / ML Operations
Strong hands-on experience with Java, Python, SQL
Experience with ML frameworks ( scikit-learn, XGBoost, TensorFlow, PyTorch )
Hands-on delivery of 3–4 production ML projects
Experience with Docker, Kubernetes, CI/CD pipelines
Familiarity with Airflow, Spark , and ML Ops frameworks
Strong communication and stakeholder management skills
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